938 resultados para Spatial Mixture Models
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Computer viruses are an important risk to computational systems endangering either corporations of all sizes or personal computers used for domestic applications. Here, classical epidemiological models for disease propagation are adapted to computer networks and, by using simple systems identification techniques a model called SAIC (Susceptible, Antidotal, Infectious, Contaminated) is developed. Real data about computer viruses are used to validate the model. (c) 2008 Elsevier Ltd. All rights reserved.
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In this work we studied the mixture of poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS), a commercial polymer, with monobasic potassium phosphate (KDP), a piezoelectric salt, as a possible novel material in the fabrication of a low cost, easy-to-make,flexible pressure sensing device. The mixture between KDP and PEDOT: PSS was painted in a flexible polyester substrate and dried. Afterwards, I x V curves were carried out. The samples containing KDP presented higher values of current in smaller voltages than the PEDOT: PSS without KDP. This can mean a change in the chain arrays. Other results showed that the material responds to directly applied pressure to the sample that can be useful to sensors fabrication. (c) 2008 Elsevier B.V. All rights reserved.
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(Spatial-temporal variation in coiled and straight morphotypes of Cylindrospermopsis raciborskii (Wolsz) Seenayya et Subba Raju (Cyanobacteria)). This study reports the spatial and temporal behavior of straight and coiled morphotypes of C. raciborskii in a reservoir in Brazil`s semiarid region as well as the main factors responsible for the variability. Two set of samples were collected from the subsurface and bottom in the central region of a reservoir in two seasonal periods (dry January 2005; rainy June 2005) over 20-hour sampling periods during daylight (8 am, 12 pm and 4 pm) and dark (8 pm, 12 am and 4 am) hours. Measurements of abiotic parameters were determined concurrently to the sampling of biotic variables. Two C. raciborskii morphotypes were found in the reservoir: straight and coiled. There was no difference in density of the straight and coiled C. raciborskii morphotypes between the different sampling times for either season. Vertical differences were found in the distribution of both morphotypes in both seasons, with greater densities recorded at the subsurface. Densities of the two C. raciborskii morphotypes were greater in the dry season, with the density of the coiled morphotype at the surface two-fold greater than that of the straight morphotype and that found in the rainy season. The ecological success of the coiled morphotype was due to thermal stratification, whereas a mixed condition was determinant in the success of the straight morphotype.
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The use of chloroplast DNA markers (cpDNA) helps to elucidate questions related to ecology, evolution and genetic structure. The knowledge of inter-and intra-population genetic structure allows to design effective conservation and management strategies for tropical tree species. With the aim to help the conservation of Hymenaea stigonocarpa of the Cerrado (Brazilian savanna) in Sao Paulo State, an analysis of the spatial genetic structure (SGS) was conducted in two populations using five universal chloroplast microsatellite loci (cpSSR). The population of 68 trees of H. stigonocarpa in the Ecological Station of Itirapina (ESI) had a single haplotype, indicating a strong founder effect. In turn, the population of 47 trees of H. stigonocarpa in a contiguous area that includes the Ecological Station of Assis and the Assis State Forest (ESA), showed six haplotypes ((n) over cap (h) = 6) with a moderate haplotype diversity ((h) over cap = 0667 + 0094), revealing that it was founded by a small number of maternal lineages. The SGS analysis for the population ESA/ASF, using Moran`s I index, indicated limited seed dispersal. Considering SGS, for ex situ conservation strategies in the population ESA/ASF, seed harvesting should require a minimum distance of 750 m among seed-trees.
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The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.
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In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.
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Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.
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In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.
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This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.
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The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved
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In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.
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The representation of sustainability concerns in industrial forests management plans, in relation to environmental, social and economic aspects, involve a great amount of details when analyzing and understanding the interaction among these aspects to reduce possible future impacts. At the tactical and operational planning levels, methods based on generic assumptions usually provide non-realistic solutions, impairing the decision making process. This study is aimed at improving current operational harvesting planning techniques, through the development of a mixed integer goal programming model. This allows the evaluation of different scenarios, subject to environmental and supply constraints, increase of operational capacity, and the spatial consequences of dispatching harvest crews to certain distances over the evaluation period. As a result, a set of performance indicators was selected to evaluate all optimal solutions provided to different possible scenarios and combinations of these scenarios, and to compare these outcomes with the real results observed by the mill in the study case area. Results showed that it is possible to elaborate a linear programming model that adequately represents harvesting limitations, production aspects and environmental and supply constraints. The comparison involving the evaluated scenarios and the real observed results showed the advantage of using more holistic approaches and that it is possible to improve the quality of the planning recommendations using linear programming techniques.
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Genetic variation and environmental heterogeneity fundamentally shape the interactions between plants of the same species. According to the resource partitioning hypothesis, competition between neighbors intensifies as their similarity increases. Such competition may change in response to increasing supplies of limiting resources. We tested the resource partitioning hypothesis in stands of genetically identical (clone-origin) and genetically diverse (seed-origin) Eucalyptus trees with different water and nutrient supplies, using individual-based tree growth models. We found that genetic variation greatly reduced competitive interactions between neighboring trees, supporting the resource partitioning hypothesis. The importance of genetic variation for Eucalyptus growth patterns depended strongly on local stand structure and focal tree size. This suggests that spatial and temporal variation in the strength of species interactions leads to reversals in the growth rank of seed-origin and clone-origin trees. This study is one of the first to experimentally test the resource partitioning hypothesis for intergenotypic vs. intragenotypic interactions in trees. We provide evidence that variation at the level of genes, and not just species, is functionally important for driving individual and community-level processes in forested ecosystems.
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The eriophyid mite Aceria guerreronis occurs in most coconut growing regions of the world and causes enormous damage to coconut fruits. The concealed environment of the fruit perianth under which the mite resides renders its control extremely difficult. Recent studies suggest that biological control could mitigate the problems caused by this pest. Neoseiulus paspalivorus and Proctolaelaps bickleyi are two of the most frequently found predatory mites associated with A. guerreronis on coconut fruits. Regarding biological control, the former has an advantage in invading the tight areas under the coconut fruit perianth while the latter is more voracious on the pest mites and has a higher reproductive capacity. Based on the idea of the combined use/release of both predators on coconut fruits, we studied their compatibility in spatial niche use and intraguild predation (IGP). Spatial niche use on coconut fruits was examined on artificial arenas mimicking the area under the coconut fruit perianth and the open fruit surface. Both N. paspalivorus and P. bickleyi preferentially resided and oviposited inside the tight artificial chamber. Oviposition rate of P. bickleyi and residence time of N. paspalivorus inside the chamber were reduced in the presence of a conspecific female. Residence of N. paspalivorus inside the chamber was also influenced by the presence of P. bickleyi. Both N. paspalivorus and P. bickleyi preyed upon each other with relatively moderate IGP rates of adult females on larvae but neither species yielded nutritional benefits from IGP in terms of adult survival and oviposition. We discuss the relevance of our findings for a hypothetic combined use of both predators in biological control of A. guerreronis.
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The van Genuchten expressions for the unsaturated soil hydraulic properties, first published in 1980, are used frequently in various vadose zone flow and transport applications assuming a specific relationship between the m and n soil hydraulic parameters. By comparison, probably because of the complexity of the hydraulic conductivity equations, the more general solutions with independent m and n values are rarely used. We expressed the general van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity equations in terms of hypergeometric functions, which can be approximated by infinite series that converge rapidly for relatively large values of the van Genuchten-Mualem parameter n but only very slowly when n is close to one. Alternative equations were derived that provide very close approximations of the analytical results. The newly proposed equations allow the use of independent values of the parameters m and n in the soil water retention model of van Genuchten for subsequent prediction of the van Genuchten-Mualem and van Genuchten-Burdine hydraulic conductivity models, thus providing more flexibility in fitting experimental pressure-head-dependent water content, theta(h), and hydraulic conductivity, K(h), or K(theta) data.